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Campos-Fornes, V.

Publications and source records attributed to Campos-Fornes, V..

2 recordsLinked to original sources

High-throughput single-cell CRISPRi screens stratify neurodevelopmental functions of schizophrenia-associated genes

Schizophrenia is a complex neuropsychiatric disorder with strong genetic underpinnings, yet the molecular mechanisms linking genetic risk to disrupted brain development remain poorly understood. Transcription factors (TFs) and chromatin regulators (CRs) are increasingly implicated in neuropsychiatric disorders, where their dysregulation may disrupt neurodevelopmental programs. Despite this, systematic functional interrogation in human models has been limited. Here, we combine pooled CRISPR interference (CRISPRi) screens with high- throughput single-cell multiomic profiling in hiPSC-derived neural progenitors and neurons to functionally assess 65 schizophrenia-associated genes. Based on public datasets and literature review, we selected 55 TFs and CRs, along with ten additional risk genes whose loss-of-function has been linked to schizophrenia. Our single-cell CRISPRi readouts revealed that perturbations in TFs and CRs converge on disrupting neurodevelopmental timing. CRISPRi of several factors delayed neural differentiation, whereas others, such as the knockdown of MCRS1, drove precocious neural commitment. Validation screens combined with cell cycle and metabolic indicators confirmed the differentiation-restricting or -promoting roles of these TFs and CRs. Multimodal trajectory analysis uncovered discrete transcriptional and epigenomic states representing delayed and accelerated neurodevelopment, enriched for schizophrenia GWAS loci and disease-relevant pathways. Gene regulatory network (GRN) inference identified TCF4 and ZEB1 as critical mediators opposing the neural differentiation trajectory. Functional overexpression of these TFs followed by chromatin profiling demonstrated that TCF4 restrains, while ZEB1 promotes, neural differentiation in a stage-specific and competitive manner. Furthermore, we show that MCRS1 represses ZEB1 expression, positioning MCRS1 as a key brake on premature neurodevelopment. Together, our study establishes a scalable framework that integrates genetic perturbation, single- cell multiomics, and GRN modeling to functionally annotate disease-linked genes. We reveal convergent regulatory axes that underlie altered neurodevelopmental timing in schizophrenia, offering mechanistic insights into how chromatin misregulation contributes to disease pathogenesis.

neuroscience↗

Scalable ultra-high-throughput single-cell chromatin and RNA sequencing reveals gene regulatory dynamics linking macrophage polarization to autoimmune disease

Enhancers and transcription factors (TFs) are crucial in regulating cellular processes, including disease-associated cell states. Current multiomic technologies to study these elements in gene regulatory mechanisms lack multiplexing capability and scalability. Here, we present SUM-seq, a cost-effective, scalable Single-cell Ultra-high-throughput Multiomic sequencing method for co-assaying chromatin accessibility and gene expression in single nuclei. SUM-seq enables profiling hundreds of samples at the million cell scale and outperforms current high-throughput single-cell methods. We applied SUM-seq to dissect the gene regulatory mechanisms governing macrophage polarization and explored their link to traits from genome-wide association studies (GWAS). Our analyses confirmed known TFs orchestrating M1 and M2 macrophage programs, unveiled key regulators, and demonstrated extensive enhancer rewiring. Integration with GWAS data further pinpointed the impact of specific TFs on a set of immune traits. Notably, inferred enhancers regulated by the STAT1/STAT2/IRF9 (ISGF3) complex were enriched for genetic variants associated with Crohns disease, ulcerative colitis and multiple sclerosis, and their target genes included known drug targets. This highlights the potential of SUM-seq for dissecting molecular disease mechanisms. SUM-seq offers a cost-effective, scalable solution for ultra-high-throughput single-cell multiomic sequencing, excelling in unraveling complex gene regulatory networks in cell differentiation, responses to perturbations, and disease studies.

genomics↗